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• 1. Comparison of waist circumference using the World Health Organization and National Institutes of Health protocols Archived

  Articles and reports: 82-003-X201200311707

  Geography: Canada

  Description:

  This study compares waist circumference measured using World Health Organization and National Institutes of Health protocols to determine if the results differ significantly, and whether equations can be developed to allow comparison between waist circumference taken at the two different measurement sites.

  Release date: 2012-09-20

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• 2. Variance inflation factors in the analysis of complex survey data Archived

  Articles and reports: 12-001-X201200111685

  Description:

  Survey data are often used to fit linear regression models. The values of covariates used in modeling are not controlled as they might be in an experiment. Thus, collinearity among the covariates is an inevitable problem in the analysis of survey data. Although many books and articles have described the collinearity problem and proposed strategies to understand, assess and handle its presence, the survey literature has not provided appropriate diagnostic tools to evaluate its impact on regression estimation when the survey complexities are considered. We have developed variance inflation factors (VIFs) that measure the amount that variances of parameter estimators are increased due to having non-orthogonal predictors. The VIFs are appropriate for survey-weighted regression estimators and account for complex design features, e.g., weights, clusters, and strata. Illustrations of these methods are given using a probability sample from a household survey of health and nutrition.

  Release date: 2012-06-27

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• 1. Comparison of waist circumference using the World Health Organization and National Institutes of Health protocols Archived

  Articles and reports: 82-003-X201200311707

  Geography: Canada

  Description:

  This study compares waist circumference measured using World Health Organization and National Institutes of Health protocols to determine if the results differ significantly, and whether equations can be developed to allow comparison between waist circumference taken at the two different measurement sites.

  Release date: 2012-09-20

  ---

• 2. Variance inflation factors in the analysis of complex survey data Archived

  Articles and reports: 12-001-X201200111685

  Description:

  Survey data are often used to fit linear regression models. The values of covariates used in modeling are not controlled as they might be in an experiment. Thus, collinearity among the covariates is an inevitable problem in the analysis of survey data. Although many books and articles have described the collinearity problem and proposed strategies to understand, assess and handle its presence, the survey literature has not provided appropriate diagnostic tools to evaluate its impact on regression estimation when the survey complexities are considered. We have developed variance inflation factors (VIFs) that measure the amount that variances of parameter estimators are increased due to having non-orthogonal predictors. The VIFs are appropriate for survey-weighted regression estimators and account for complex design features, e.g., weights, clusters, and strata. Illustrations of these methods are given using a probability sample from a household survey of health and nutrition.

  Release date: 2012-06-27

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